Image Model Blocks
Bottleneck Transformer Block
Introduced by Srinivas et al. in Bottleneck Transformers for Visual RecognitionA Bottleneck Transformer Block is a block used in Bottleneck Transformers that replaces the spatial 3 × 3 convolution layer in a Residual Block with Multi-Head Self-Attention (MHSA).
Source: Bottleneck Transformers for Visual Recognition
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Instance Segmentation | 2 | 16.67% |
| Classification | 1 | 8.33% |
| Emotion Recognition | 1 | 8.33% |
| Self-Supervised Learning | 1 | 8.33% |
| Semantic Segmentation | 1 | 8.33% |
| Autonomous Driving | 1 | 8.33% |
| Scene Understanding | 1 | 8.33% |
| Anatomy | 1 | 8.33% |
| General Classification | 1 | 8.33% |
1x1 Convolution
Multi-Head Attention
Pointwise Convolution
Residual Connection
Scaled Dot-Product Attention
